| Literature DB >> 33029768 |
Himanshu Agrawal1, Neeladrisingha Das1, Sandip Nathani1, Sarama Saha2, Surendra Saini1, Sham S Kakar3, Partha Roy4.
Abstract
Coronavirus disease 2019 (COVID-19) is caused by novel coronavirus Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was first time reported in December 2019 in Wuhan, China and thereafter quickly spread across the globe. Till September 19, 2020, COVID-19 has spread to 216 countries and territories. Severe infection of SARS-CoV-2 cause extreme increase in inflammatory chemokines and cytokines that may lead to multi-organ damage and respiratory failure. Currently, no specific treatment and authorized vaccines are available for its treatment. Renin angiotensin system holds a promising role in human physiological system specifically in regulation of blood pressure and electrolyte and fluid balance. SARS-CoV-2 interacts with Renin angiotensin system by utilizing angiotensin-converting enzyme 2 (ACE2) as a receptor for its cellular entry. This interaction hampers the protective action of ACE2 in the cells and causes injuries to organs due to persistent angiotensin II (Ang-II) level. Patients with certain comorbidities like hypertension, diabetes, and cardiovascular disease are under the high risk of COVID-19 infection and mortality. Moreover, evidence obtained from several reports also suggests higher susceptibility of male patients for COVID-19 mortality and other acute viral infections compared to females. Analysis of severe acute respiratory syndrome coronavirus (SARS) and Middle East respiratory syndrome coronavirus (MERS) epidemiological data also indicate a gender-based preference in disease consequences. The current review addresses the possible mechanisms responsible for higher COVID-19 mortality among male patients. The major underlying aspects that was looked into includes smoking, genetic factors, and the impact of reproductive hormones on immune systems and inflammatory responses. Detailed investigations of this gender disparity could provide insight into the development of patient tailored therapeutic approach which would be helpful in improving the poor outcomes of COVID-19. Graphical abstract.Entities:
Keywords: COVID-19; Coronavirus-2; Gender; Mesenchymal stem cells; Severe acute respiratory syndrome (SARS); Spike protein; Transmembrane protease serine-2
Mesh:
Substances:
Year: 2020 PMID: 33029768 PMCID: PMC7541100 DOI: 10.1007/s12015-020-10048-z
Source DB: PubMed Journal: Stem Cell Rev Rep ISSN: 2629-3277 Impact factor: 5.739
Fig. 1Possible transmission route of SARS-CoV-2 from bat to human
Fig. 2(a) Structure of SARS-CoV-2; (b) Mechanism of virus entry into cells and its mode of replication. Adopted from Jiang et al. (2020) [153]
Fig. 3RAS system and its interaction with SARS-CoV-2. Adopted from Vaduganathan et al. 2020 [6]
Sex segregated data for COVID-19 cases and death for highly affected countries wherever available (Countries with minimum value of death ratio: 1.4 are only included in this table)
| Sr. No. | Country | Cases where sex-segregated data available | Case % (Male) | Case % (Female) | Deaths, where sex segregated data available | Death % (Male) | Death % (Female) | Case fatality rate (Male) | Case fatality rate (Female) | Death ratio (Male: Female) in confirmed cases |
|---|---|---|---|---|---|---|---|---|---|---|
| Thailand | 3148 | 55 | 44.89 | 58 | 76.00 | 24.00 | 2.54 | 0.98 | 2.6 | |
| Costa Rica | 2277 | 56 | 44.18 | 9 | 75.00 | 25.00 | 0.53 | 0.22 | 2.4 | |
| Albania | 2047 | 47 | 53.00 | 30 | 67.00 | 33.00 | 2.08 | 0.91 | 2.3 | |
| The Netherlands | 49,631 | 37.55 | 62.45 | 6095 | 55.03 | 44.97 | 17.99 | 8.84 | 2 | |
| Bosnia and Herzegovina | 1676 | 46.36 | 53.64 | 47 | 61.70 | 38.30 | 3.73 | 2.00 | 1.9 | |
| Haiti | 5211 | 59.51 | 40.49 | 65 | 73.86 | 26.14 | 1.55 | 0.81 | 1.9 | |
| North Macedonia | 3363 | 48.80 | 51.20 | 259 | 64.09 | 35.91 | 10.11 | 5.40 | 1.9 | |
| Denmark | 12,561 | 42.54 | 57.46 | 603 | 56.72 | 43.28 | 6.40 | 3.61 | 1.8 | |
| Dominican Republic | 27,370 | 54.06 | 45.94 | 669 | 68.16 | 31.84 | 3.08 | 1.69 | 1.8 | |
| England | 228,742 | 43.02 | 56.98 | 37,664 | 57.13 | 42.87 | 21.87 | 12.39 | 1.8 | |
| Greece | 3085 | 54.81 | 45.19 | 190 | 68.42 | 31.58 | 7.69 | 4.30 | 1.8 | |
| Latvia | 1111 | 52.12 | 47.88 | 20 | 67.00 | 33.00 | 2.31 | 1.24 | 1.9 | |
| Northern Ireland | 4861 | 38.06 | 61.94 | 545 | 52.29 | 47.71 | 15.40 | 8.64 | 1.8 | |
| Romania | 22,160 | 44.51 | 55.49 | 1427 | 59.00 | 41.00 | 8.54 | 4.76 | 1.8 | |
| Spain | 248,335 | 42.99 | 57.01 | 20,527 | 56.53 | 43.43 | 10.87 | 6.30 | 1.7 | |
| Sweden | 60,837 | 40.63 | 59.37 | 5161 | 54.76 | 45.24 | 11.43 | 6.46 | 1.8 | |
| Belgium | 60,567 | 37.10 | 62.90 | 7016 | 50.50 | 49.50 | 15.77 | 9.11 | 1.7 | |
| China | 55,924 | 51.10 | 48.90 | 2114 | 63.53 | 36.23 | 4.69 | 2.80 | 1.7 | |
| Italy | 238,050 | 45.79 | 54.21 | 33,209 | 58.25 | 41.75 | 17.75 | 10.75 | 1.7 | |
| Peru | 257,447 | 58.20 | 41.80 | 8223 | 70.84 | 29.16 | 3.89 | 2.23 | 1.8 | |
| Burkina Faso | 934 | 64.13 | 35.87 | 38 | 74.51 | 25.49 | 4.73 | 2.90 | 1.6 | |
| Ecuador | 29,615 | 55.54 | 44.46 | 3334 | 66.41 | 33.59 | 13.46 | 8.50 | 1.6 | |
| Mexico | 185,122 | 55.03 | 44.97 | 22,584 | 66.09 | 33.91 | 14.65 | 9.20 | 1.6 | |
| Scotland | 18,038 | 37.99 | 62.01 | 4119 | 49.79 | 50.21 | 29.93 | 18.49 | 1.6 | |
| Switzerland | 31,306 | 45.83 | 54.17 | 1680 | 57.56 | 42.44 | 6.74 | 4.20 | 1.6 | |
| Ukraine | 9410 | 44.00 | 56.00 | 239 | 55.23 | 44.77 | 3.19 | 2.03 | 1.6 | |
| Afghanistan | 25,987 | 72.52 | 27.48 | 423 | 79.43 | 20.57 | 1.78 | 1.22 | 1.5 | |
| South Korea | 12,484 | 42.57 | 57.43 | 281 | 53.38 | 46.62 | 2.82 | 1.82 | 1.5 | |
| Bangladesh | 115,786 | 71.00 | 29.00 | 1502 | 77.03 | 22.97 | 1.41 | 1.02 | 1.4 | |
| Czech Republic | 10,182 | 50.22 | 49.78 | 339 | 58.11 | 41.89 | 3.85 | 2.80 | 1.4 | |
| Indonesia | 47,896 | 52.70 | 47.30 | 2535 | 60.60 | 39.40 | 6.09 | 4.40 | 1.4 | |
| Kenya | 4738 | 69.00 | 31.00 | 123 | 76.00 | 24.00 | 2.86 | 2.01 | 1.4 | |
| South Africa | 105,308 | 42.90 | 57.10 | 2100 | 51.76 | 48.24 | 2.41 | 1.69 | 1.4 |
Case fatality rate (Male) = Number of death (Male) / Total number of cases (Male) X 100
Case fatality rate (Female) = Number of death (Female) / Total number of cases (Female) X100
Data Source and credit to: Global Health 50/50 [28]
Fig. 4Possible reasons which may be responsible for high mortality rate in males infected with COVID-19
Differences in smoking rate in men and women in various sub-continents across the globe
| Continent/Countries | Smokers (Male %) | Smokers (Female %) | Male: Female ratio | |
|---|---|---|---|---|
| Globally | 35 | 6 | 5.8 | |
| South Africa | 33.2 | 8 | 4.2 | |
| Tunisia | 65.8 | 1.1 | 59.8 | |
| Egypt | 50.1 | 0.2 | 250.5 | |
| Ethiopia | 8.5 | 0.4 | 21.3 | |
| Uganda | 16.7 | 3.4 | 4.9 | |
| Liberia | 18.1 | 1.5 | 12 | |
| Morocco | 47.1 | 0.8 | 58.9 | |
| Nigeria | 10.8 | 0.6 | 18 | |
| China | 48.4 | 1.9 | 25.5 | |
| Indonesia | 76.1 | 2.8 | 27.2 | |
| Turkey | 41.1 | 14.1 | 2.9 | |
| India | 20.6 | 1.9 | 10.8 | |
| Vietnam | 45.9 | 1.0 | 45.9 | |
| Japan | 33.7 | 11.2 | 3.0 | |
| Bangladesh | 44.7 | 1.0 | 44.7 | |
| Malaysia | 42.4 | 1.1 | 38.5 | |
| Pakistan | 36.7 | 2.8 | 13.1 | |
| Chile | 41.5 | 34.2 | 1.2 | |
| Brazil | 17.9 | 10.1 | 1.8 | |
| Columbia | 13.5 | 4.7 | 2.9 | |
| Ecuador | 12.3 | 2 | 6.2 | |
| United Sates | 24.6 | 19.1 | 1.3 | |
| Mexico | 21.4 | 6.9 | 3.1 | |
| Columbia | 13.5 | 4.7 | 2.9 | |
| Canada | 16.6 | 12 | 1.4 | |
| Poland | 33 | 23 | 1.4 | |
| Netherland | 27.3 | 24.4 | 1.1 | |
| Ireland | 25.7 | 23 | 1.1 | |
| Slovania | 25 | 20.1 | 1.2 | |
| Germany | 33.1 | 28.2 | 1.2 | |
| Spain | 31.4 | 27.4 | 1.1 | |
| Austria | 30.9 | 28.4 | 1.1 | |
| Sweden | 18.9 | 18.8 | 1.0 | |
| Greece | 52 | 35.3 | 1.5 | |
| Australia | 16.5 | 13 | 1.3 | |
| New Zeeland | 17.2 | 14.8 | 1.2 | |
| Fiji | 34.8 | 10.2 | 3.4 | |
Data source and credit to: Hannah R and Max R (2013) (Reference No. 41)
Male: Female ratio = Percentage of male smokers/percentage of female smokers